The State of AI in Marketing and Advertising
55 marketing and media professionals told us exactly where AI is working, where it's falling short, and what the gap between excitement and execution actually looks like.
Key Findings
AI is saving time. It's not yet driving growth.
Time savings and efficiency dominate how organizations measure AI's value, but tactical metrics like revenue, pipeline impact and customer outcomes barely register. Companies in every respondent category are still in the stage where AI helps people work faster, but most organizations haven't yet wired AI to the metrics that actually move the business.
Content creation is way out front. Media planning is way behind.
More than half of respondents have reached an advanced maturity level in content creation — by far the furthest-along function in the survey. Meanwhile, only 18% report meaningful AI use in media planning and buying. The pattern suggests that AI is winning where humans can quickly review and course-correct, and stalling where the systems are complex and the cost of error is high.
Agencies are pulling ahead — and it's probably because they know they have to.
Among segments with meaningful response volume, agencies report the most advanced maturity and are most likely to describe AI as delivering ROI. Brands and consultancies cluster significantly behind. One theory on this disparity is that agencies face constant pressure to produce faster and serve clients more efficiently. Results suggest agencies know they need to embed AI to remain relevant and competitive.
Everyone is moving fast. Few are keeping score.
AI adoption is accelerating across the marketing industry, but a striking 24% of respondents say they are not currently measuring its impact in any meaningful way. That number climbs even higher among larger organizations, where change management complexity outpaces the speed of implementation. The industry has embraced the language of transformation faster than it has built the discipline to track it.
The #1 barrier isn't the technology. It's the team.
Skills, resources and budget were cited by 82% of respondents — by a wide margin the most common obstacle. Governance, compliance and data quality ranked far lower. The market is not short on AI tools. It is short on teams that know how to use those tools consistently, in ways that fit real workflows and connect to real outcomes. That gap is harder to close than any product feature.
Most organizations are still somewhere between experimenting and committed.
A large share of respondents are testing, piloting or implementing without measuring ROI. We call this, "throwing spaghetti against the wall and hoping something sticks." Survey results indicate that the industry has embraced the language of AI transformation faster than it has built the discipline to make that transformation real. Without KPIs, economic benefits will be achieved by chance instead of by design.
What organizations need next isn't more tools. It's repeatable systems.
The next competitive advantage won't come from finding a better platform — it will come from embedding AI into workflows, decision-making and measurement in ways that are consistent and scalable. The companies that pull ahead won't be the ones with the most tools. They'll be the ones that have turned their experiments into an operating model.
Want to explore the results yourself?
These are just a few of the headlines. The complete survey analysis tool lets you filter results by organization type, company size and role, to compare maturity across functions, and to drill into the verbatim responses behind the numbers.
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